Interview Q&A · 12 questions · 2 answered publicly
AI-Assisted Development Interview Questions
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Most asked How do you use AI coding assistants effectively without lowering code quality?
Summary
Give them the right context (project instructions, example files, constraints), ask for small steps with a plan first, define done with tests, and review everything they produce as carefully as a colleague's code: run it, read every line, test edge cases, check dependencies and security.
Longer Answer
The productivity gain comes from the assistant doing the typing and boilerplate while you keep ownership of design, correctness and review. Teams that treat "generated by AI" as a reason to review less see more incidents; teams that pair assistants with tests-first workflows and small PRs see faster delivery without quality loss.
Key Points
- Context in, quality out.
- Plan first, small steps.
- Tests define done.
- Review like a colleague's code.
Deep dive: Coding with AI Assistants
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Most asked How do you review a pull request that was largely written by AI?
Summary
The same way as any PR, with extra attention to what assistants get wrong: run the code and tests yourself, read every line, test edge cases the generated tests skip, verify every new dependency exists and is the intended package, check for injection, weak defaults and secrets, and make sure the author can explain the code.
Longer Answer
Generated tests often mirror the implementation and cover only the happy path, so they are weak evidence. Large AI-generated PRs should be split; reviewers can't meaningfully review 900 lines. The author owns the code regardless of who typed it.
Key Points
- Run, read, test edge cases.
- Distrust tests generated with the code.
- Check dependencies and security.
- Author must understand it; keep PRs small.
Deep dive: Reviewing AI-Written Code
- What context should you give an AI coding assistant, and how?
- What is package hallucination (slopsquatting), and how do you protect against it?
- How would you use an AI assistant for test-driven development?
- What are the risks of agentic coding tools, and how do you control them?
- What should never be pasted into an AI assistant, and what do you do if it happens?
- How should a team measure the impact of AI coding tools?
- How do you refactor legacy code safely with an AI assistant?
- How do you debug effectively with an AI assistant?
- Will relying on AI assistants erode a developer's skills? How do you prevent it?
- How do licensing concerns apply to AI-generated code?